Discrimination of the degree of roasting and quality prediction of Tieguanyin oolong tea based on NIRS, E-nose, and data fusion

Key Points

• Quality prediction utilizes a combination of NIRS and E-nose data for enhanced accuracy.
• Degree of roasting significantly influences the resulting flavor profile of Tieguanyin oolong tea.
• Assessment employed data fusion techniques to analyze aromatic compounds and spectral data.
• Findings highlight potential for innovative quality evaluation methods in tea production.